摘要
目的探讨器官剂量调制(ODM)技术在胸部CT扫描中对降低乳腺器官剂量的作用。方法模体研究采用PBU-2成人胸部拟人模体,使用临床胸部扫描参数,均开启智能毫安调制(Smart mA),在其他参数相同情况下对胸部模体进行3组扫描:(1)ODM off组,不使用ODM技术;(2)ODM part组,在乳腺区域开启ODM;(3)ODM all组,全扫描范围开启ODM。记录容积CT剂量指数(CTDIvol);并于右侧乳腺区域前方固定位置放置长杆电离室,测量乳腺皮肤剂量值D;计算图像对比噪声比(CNR)和品质因子(FOM)。临床研究中,回顾性收集2018年8月至11月于首都医科大学附属北京同仁医院行胸部CT平扫的72例女性患者,分为ODM off组(不使用ODM技术)和ODM part组(乳腺区域使用ODM),均为36例。记录CTDIvol和剂量长度乘积(DLP),测量并计算图像CNR、噪声并对图像质量进行主观评分。3组模体图像CNR的比较采用单因素方差分析;对临床研究中2组患者间CTDIvol、DLP、CNR、噪声比较采用独立样本t检验,对主观评分比较采用秩和检验。结果模体研究中,ODM off、ODM part和ODM all组扫描剂量依次下降,CTDIvol分别为(6.90±0.02)、(6.26±0.02)、(5.99±0.02)mGy,乳腺皮肤剂量D为(9.17±1.01)、(8.01±0.92)、(7.58±0.87)mGy;软组织算法图像CNR依次降低,差异无统计学意义(P>0.05)。肺算法图像CNR依次降低,差异有统计学意义(F=154.732,P=0.006)。肺及软组织算法图像FOM均在部分开启ODM时最大。临床研究中,与ODM off组比较,ODM part组CTDIvol下降16.12%,DLP下降16.85%,差异均有统计学意义(CTDIvol:t=2.604,P=0.011;DLP:t=3.293,P=0.002);图像CNR、噪声及2名医师主观评分差异均无统计意义(P>0.05)。结论在胸部CT扫描中使用ODM技术可在保持较高影像质量情况下进一步降低乳腺辐射剂量。
Objective To investigate the effect of organ dose modulation(ODM)technique on reducing the breast radiation dose in chest CT scanning.Methods In the phantom test,the PBU-2 adult chest module was used.The clinical chest scan protocol was used and three sets of scans performed on the chest module:(1)ODM off group,ODM was not used;(2)ODM part group,ODM was applied only in the breast region;(3)ODM all group,ODM was applied in the whole scan scope.Other scan parameters were same for the three groups,with smart mA applied.The volume CT dose index(CTDIvol)was recorded for all three groups.A long rod ionization chamber was placed in a fixed position in front of the right breast area to measure the breast skin dose(D).The contrast noise ratio(CNR)and the figure of merit(FOM)were measured respectively.In clinical research,72 female patients who underwent chest CT scanning in Beijing Tongren Hospital Capital Medical University from August to November 2018 were retrospectively recruited.According to the application of ODM,the patients were divided into ODM off group(without ODM,36 cases)and ODM part group(ODM applied in the breast region,36 cases).The CTDIvol and the dose length product(DLP)were recorded.CNR,noise of images were measured and calculated,respectively.The image quality was evaluated by subjective evaluation scores.The one way ANOVA analysis was used in comparing the difference of CNR among the 3 groups in module test.As for clinical cases,the independent samples t test was used to compare the difference in CTDIvol,DLP,CNR and the noise between two groups;and the rank-sum test was used for comparison in image quality subjective evaluation.Results In module test,the radiation dose was highest in ODM off group,and lowest in ODM all group.The CTDIvol were(6.90±0.02),(6.26±0.02)and(5.99±0.02)mGy,and the D values were(9.17±1.01),(8.01±0.92)and(7.58±0.87)mGy for ODM off group,ODM part group and ODM all group respectively.The CNR values of images with soft tissue algorithm reconstruction were highest in ODM off group and lowest in ODM all group,while no statistically significant difference was displayed(P>0.05).The CNR values of the images with lung algorithm reconstruction showed the same trend,with statistically significant difference among the three groups(F=154.732,P=0.006).The FOM of the lung and soft tissue algorithm images was maximized when the ODM was partially applied.As for clinical cases,compared with ODM off group,the dose of ODM part group showed significantly decreased,with CTDIvol decreased by 16.12%(t=2.604,P=0.011),and the DLP decreased by 16.85%(t=3.293,P=0.002).No significant difference was found in CNR,noise and subjective score by two doctors between two groups(P>0.05).Conclusion The application of ODM in chest CT imaging can reduce the radiation dose of breast with simultaneously maintaining the image quality.
作者
张永县
牛延涛
张丽丽
郭森林
刘丹丹
虞滨滨
吴建兴
康天良
王世军
李伟
Zhang Yongxian;Niu Yantao;Zhang Lili;Guo Senlin;Liu Dandan;Yu Binbin;Wu Jianxing;Kang Tianliang;Wang Shijun;Li Wei(Department of Radiology,Beijing Tongren Hospital,Capital Medical University,Beijing 100730,China)
出处
《中华放射学杂志》
CAS
CSCD
北大核心
2020年第6期587-591,共5页
Chinese Journal of Radiology
基金
北京市卫生系统高层次卫生技术人才培养计划(20143019)
北京市医院管理局临床医学发展专项经费(ZYLX201704)。